Imagery from remote sensing systems is able to provide repetitive, synoptic views of soil moisture and crop water status. When the source of remote sensing data is medium-resolution satellite imagery, soil and canopy characteristics can be estimated for numerous fields within an agricultural region. In this study, a simplified land surface dryness index (Perpendicular Moisture stress Index, PMSI) for soil moisture and crop water status monitoring is suggested. PMSI is based on the relation between raw Thermal irradiance (TIR) and Ground cover (GC) information. First, the TIR–GC space is established using geometrically corrected ETM+ data, which results in a Triangle/Trapezoid shape and in which different surface targets possess certain spatial distribution characteristics. Second, the Perpendicular Soil Moisture Index (PSMI) is evaluated on the basis of spatial characteristics of moisture distribution in the TIR-GC space. Unlike previous methods, this method does not depend on empirical relationships. The index is related to soil moisture and, in comparison to existing interpretations of the Temperature-NDVI space, the index is conceptually and computationally straightforward. It is based on satellite-derived information only, and the potential for operational application of the index is therefore great. The procedure was evaluated and tested using data from a field study conducted in 2008, 2010 and 2012 in the Texas High Plains. PMSI for the fields in the study were estimated using image data from the Landsat-5 TM and Landsat-7 Enhanced Thematic Mapper plus (ETM+). The results suggest that, on average, estimates of soil moisture and crop water status determined using this procedure should be in reasonable agreement with their true values.